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cs.CV2025

Align Your Query: Representation Alignment for Multimodality Medical Object Detection

Ara Seo, Bryan Sangwoo Kim, Hyungjin Chung +1

Medical object detection suffers when a single detector is trained on mixed medical modalities (e.g., CXR, CT, MRI) due to heterogeneous statistics and disjoint representation spac…

cs.CV2025

Extreme Blind Image Restoration via Prompt-Conditioned Information Bottleneck

Hongeun Kim, Bryan Sangwoo Kim, Jong Chul Ye

Blind Image Restoration (BIR) methods have achieved remarkable success but falter when faced with Extreme Blind Image Restoration (EBIR), where inputs suffer from severe, compounde…

cs.CV2025

FlowAlign: Trajectory-Regularized, Inversion-Free Flow-based Image Editing

Jeongsol Kim, Yeobin Hong, Jonghyun Park +1

Recent inversion-free, flow-based image editing methods such as FlowEdit leverages a pre-trained noise-to-image flow model such as Stable Diffusion 3, enabling text-driven manipula…

cs.CV2025

Chain-of-Zoom: Extreme Super-Resolution via Scale Autoregression and Preference Alignment

Bryan Sangwoo Kim, Jeongsol Kim, Jong Chul Ye

Modern single-image super-resolution (SISR) models deliver photo-realistic results at the scale factors on which they are trained, but collapse when asked to magnify far beyond tha…

cs.CV2025

FlowDPS: Flow-Driven Posterior Sampling for Inverse Problems

Jeongsol Kim, Bryan Sangwoo Kim, Jong Chul Ye

Flow matching is a recent state-of-the-art framework for generative modeling based on ordinary differential equations (ODEs). While closely related to diffusion models, it provides…

cs.CV2025

Aligning Text to Image in Diffusion Models is Easier Than You Think

Jaa-Yeon Lee, Byunghee Cha, Jeongsol Kim +1

While recent advancements in generative modeling have significantly improved text-image alignment, some residual misalignment between text and image representations still remains.…